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DOE OSTI2022

Highly tunable band inversion in AB 2 X 4 (A=Ge, Sn, Pb; B=As, Sb, Bi; X=Se, Te) compounds

Topological materials have been discovered so far largely by searching for existing compounds in crystallographic databases, but there are potentially new topological materials with desirable features that have not been synthesized. One of the desirable features is high tunability resulting from the band inversion with a very small direct band gap, which can be tuned by changes in pressure or strain to induce a topological phase transition. Here, using density-functional theory (DFT) calculations, we have studied the septuple layered AB 2 X 4 series compounds, where A=(Ge, Sn and Pb), B=(As, Sb and Bi), and X=(Se and Te). With the DFT thermodynamic stability validated by the already-reported compounds in these series, we predict stable Se compounds, which are not found in crystallographic database. Among them, we find that GeBi 2 Se 4 and GeSb 2 Se 4 having a small direct band gap at the Z point are very close to a strong topological insulator, which can be tuned by a moderate pressure to induce the band inversion. Importantly, the topological features with the small direct band gap are well isolated in both momentum and energy windows, which offers high tunability for studying the topological phase transition.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Structure and electronic tunability of acene alkylamine based layered hybrid organic-inorganic perovskites from first principles

Twelve layered hybrid organic-inorganic perovskites combining oligoacene derivatives [phenylmethylammonium (PMA), naphthylmethylammonium (NMA), anthrylmethylammonium (AMA), and tetrylmethylammonium (TMA)] and lead halides (Cl - , Br - , and I - anions) are investigated by first-principles density functional theory (DFT), showing broad, rational tunability of band gap, quantum well type, and spin-dependent energy band properties. Six compounds are known from previous syntheses and are used to devise a computational search space for likely low-energy structures. Among the six known compounds, a refined structure is identified for (NMA) 2 ⁢ PbCl 4 and a new, lower-energy structure is suggested for (AMA) 2 ⁢PbCl 4 . The DFT based search methodology is next applied to predict the likely structures for the six unknown compounds. Computationally predicted energy levels for all 12 compounds from spin-orbit coupled hybrid DFT reveal tunable type I quantum well alignments, with frontier orbitals located on the inorganic component, on the organic component, or on both, as controlled by cation and anion selection. In conclusion, several structures spontaneously break local and global inversion symmetry, causing strong spin splitting of the conduction bands [up to 0.12 eV for (PMA) 2 ⁢PbCl 4 ] and showing potential for spin-dependent transport properties and future spintronic and tunable chiroptical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Structural Stability of Tin-Lead Halide Perovskite Solar Cells

One of the key features that makes halide perovskite solar cells such an attractive and intensely researched photovoltaic (PV) technology, is the tunability of the bandgap of these halide perovskite materials [1], [2]. Shortly after it was established that the bandgap could be increased to 1.7-1.8 eV, investigations into the application for silicon based tandem solar cells launched. Within a few years, conversion efficiencies of up to 28 % have been reported [3]. Concurrently, the interest in commercial application of this technology emerged and have rapidly increased. Whereas there are advantages to piggy backing on an established PV technology such as silicon, efforts to develop all-perovskite tandem solar cells are of considerable interest. Partly substituting the metal cation in the ABX3 perovskite enables the low bandgap absorbers required for an all-perovskite tandem solar cell. One common approach is to partially substitute the lead with tin, however these materials often suffered from poor stability. Therefore the development of an efficient, stable mixed tin-lead perovskite is key to enabling all-perovskite tandem solar cells.

degradation↗

DOE OSTI2023

Auger spectroscopy beyond the ultra-short core-hole relaxation time approximation

Abstract We present a time-dependent computational approach to study Auger electron spectroscopy (AES) beyond the ultra-short core-hole relaxation time approximation and, as a test case, we apply it to the paradigmatic example of a one-dimensional Mott insulator represented by a half-filled Hubbard chain. The Auger spectrum is usually calculated by assuming that, after the creation of a core-hole, the system thermalizes almost instantaneously. This leads to a relatively simple analytical expression that uses the ground-state with a core-hole as a reference state and ignores all the transient dynamics related to the screening of the core-hole. In this picture, the response of the system can be associated to the pair spectral function. On the other hand, in our numerical calculations, the core hole is created by a light pulse, allowing one to study the transient dynamics of the system in terms of the pulse duration and in the non-perturbative regime. Time-dependent density matrix renormalization group calculations reveal that the relaxation process involves the creation of a polarization cloud of doublon excitations that have an effect similar to photo-doping. As a consequence, there is a leak of spectral weight to higher energies into what otherwise would be the Mott gap. For longer pulses, these excited states, mostly comprised of doublons, can dominate the spectrum. By changing the duration of the light-pulse, the entire screening process can be resolved in time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Machine Learning for Sustainable Energy Systems

In recent years, machine learning has proven to be a powerful tool for deriving insights from data. In this review, we describe ways in which machine learning has been leveraged to facilitate the development and operation of sustainable energy systems. We first provide a taxonomy of machine learning paradigms and techniques, along with a discussion of their strengths and limitations. We then provide an overview of existing research using machine learning for sustainable energy production, delivery, and storage. Finally, we identify gaps in this literature, propose future research directions, and discuss important considerations for deployment.

Environmental Sciences & Ecology↗

DOE OSTI2023

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Nitrogen Vacancy Center in Diamond for the Stress and Field Sensing Applications

The nitrogen-vacancy (NV) center in a nanodiamond (ND) crystal is a promising material for quantum information processing, sensing, and computing applications. It is one of the best candidate materials for quantum sensing and metrology expected to work at elevated temperatures and pressures conditions. We computationally show the effect of strain on the defect band edges and band gaps in the NV center diamond. A low energy Hamiltonian is developed for the ±1 spin manifold at the ground state. We show the quantum sensing device is a few orders of magnitude superior in sensing than the traditional optical sensing devices. We also discuss experimental results from the optically detected magnetic resonance (ODMR) and the spin relaxometry for the field sensing applications. The presentation concludes by providing a model for free spins detection of the rare earth ions.

field sensing applications↗

DOE OSTI2025

Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model

Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes across atmosphere–land–river–ocean systems, leading to substantial uncertainties that have not been fully examined. To bridge this gap, we leverage the new capabilities of the Energy Exascale Earth System Model (E3SM) that enable a multi-component framework that integrates coastally refined atmospheric, terrestrial, and oceanic components. We evaluate compound uncertainties arising from two-way land–river–ocean coupling in E3SM and track the cascading meteorological and hydrological uncertainties through ensemble simulations over the Delaware River basin and estuary during Hurricane Irene (2011). Our findings highlight the importance of two-way river–ocean coupling to compound flood modeling and demonstrate E3SM's capability in capturing compound flood extent near the coast, with a hit rate over 0.75. Our study shows the growing uncertainties that transition from atmospheric forcings to flood distribution and severity. Furthermore, an analysis based on artificial neural networks is used to assess the roles of hydrological drivers, such as infiltration and soil moisture, in the generation of compound flooding. The response of compound floods to tropical cyclones (TCs) is found to be susceptible to these often overlooked drivers. For instance, the flooded area could increase more than 2-fold (∼2.4) if Hurricane Irene were preceded by an extreme antecedent soil moisture condition (AMC). The results not only support the use of a multi-component framework for interactive flooding processes, but also underscore the necessity of broader definitions of compound flooding that encompass the simultaneous occurrence of intense precipitation, storm surge, and high AMC during TCs.

Feng, Dongyu [Pacific Northwest National Laborator↗

DOE OSTI2022

Hot Electron-Driven Photocatalysis Using Sub-5 nm Gap Plasmonic Nanofinger Arrays

Semiconductor photocatalysis has received increasing attention because of its potential to address problems related to the energy crisis and environmental issues. However, conventional semiconductor photocatalysts, such as TiO2 and ZnO, can only be activated by ultraviolet light due to their wide band gap. To extend the light absorption into the visible range, the localized surface plasmon resonance (LSPR) effect of noble metal nanoparticles (NPs) has been widely used. Noble metal NPs can couple incident visible light energy to strong LSPR, and the nonradiative decay of LSPR generates nonthermal hot carriers that can be injected into adjacent semiconductor material to enhance its photocatalytic activity. Here we demonstrate that nanoimprint-defined gap plasmonic nanofinger arrays can function as visible light-driven plasmonic photocatalysts. The sub-5 nm gaps between pairs of collapsed nanofingers can support ultra-strong plasmon resonance and thus boost the population of hot carriers. The semiconductor material is exactly placed at the hot spots, providing an efficient pathway for hot carrier injection from plasmonic metal to catalytic materials. This nanostructure thus exhibits high plasmon-enhanced photocatalytic activity under visible light. The hot carrier injection mechanism of this platform was systematically investigated. The plasmonic enhancement factor was calculated using the finite-difference time-domain (FDTD) method and was consistent with the measured improvement of the photocatalytic activity. This platform, benefiting from the precise controllable geometry, provides a deeper understanding of the mechanism of plasmonic photocatalysis.

42 ENGINEERING↗

DOE OSTI2024

Analytic Gradients for Equation-of-Motion Coupled Cluster with Single, Double, and Perturbative Triple Excitations

Understanding the process of molecular photoexcitation is crucial in various fields, including drug development, materials science, photovoltaics, and more. The electronic vertical excitation energy is a critical property, for example in determining the singlet-triplet gap of chromophores. However, a full understanding of excited-state processes requires additional explorations of the excited-state potential energy surface and electronic properties, which is greatly aided by the availability of analytic energy gradients. Owing to its robust high accuracy over a wide range of chemical problems, equation-of-motion coupled-cluster with single and double excitations (EOM-CCSD) is a powerful method for predicting excited state properties, and the implementation of analytic gradients of many EOM-CCSD (excitation energies, ionization potentials, electron attachment energies, etc.) along with numerous successful applications high- lights the flexibility of the method. In specific cases where a higher level of accuracy is needed or in more complex electronic structures, the inclusion of triple excitations becomes essential, for example, in the EOM-CCSD* approach of Saeh and Stanton. In this work, we derive and implement for the first time the analytic gradients of EOMEE-CCSD*, which also provides a template for analytic gradients of related ex- cited state methods with perturbative triple excitations. Here, the capabilities of analytic EOMEE-CCSD* gradients are illustrated by several representative examples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A Comparison of Time-Series Gap-Filling Methods to Impute Solar Radiation Data: Preprint

Complete solar resource data sets play a critical role at every stage of solar energy projects; however, measured or modeled solar resource data come with significant uncertainties and usually suffer from several issues, including, but not limited to, data gaps and data quality issues. To mitigate these issues, an appropriate data imputation method should be implemented to build a complete and reliable temporal (and spatial) database. Motivated by this, in this study, we extensively compare the performance of eight different gap-filling methods by creating random and artificial data gaps in (i) hourly irradiance data for 1 year using a few locations of the National Solar Radiation Database (NSRDB) and (ii) 1-minute ground measurement data sets from the Surface Radiation Budget Network (SURFRAD) and the National Renewable Energy Laboratory (NREL) stations.

clearness index↗

DOE OSTI2020

Quantifying the impacts of climate change and extreme climate events on energy systems

Climate induced extreme weather events and weather variations will affect both the demand of energy and the resilience of energy supply systems. The specific potential impact of extreme events on energy systems has been difficult to quantify due to the unpredictability of future weather events. In this work, we develop a stochastic-robust optimization method to consider both low impact variations and extreme events. Applications of the method to 30 cities in Sweden, by considering 13 climate change scenarios, reveal that uncertainties in renewable energy potential and demand can lead to a significant performance gap (up to 34% for grid integration) brought by future climate variations and a drop in power supply reliability (up to 16%) due to extreme weather events. Finally, appropriate quantification of the climate change impacts will ensure robust operation of the energy systems and enable renewable energy penetration above 30% for a majority of the cities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Energy Justice in Low-TRL Research

The Carbon-Negative Hydrogen Workshop, hosted by NREL in Golden, Colorado, focused on developing a shared understanding of the importance of and opportunities for generation and use of carbon-negative H2 in industrial decarbonization. Attendees helped define research needs, spot barriers to commercialization, and identify technical challenges, opportunities, and knowledge gaps for this emerging technology area. Workshop discussion themes included energy justice in early-stage research, R&D pathways for negative-emissions H2, biomass gasification to carbon-negative H2, and policy and carbon accounting considerations.

carbon-negative hydrogen↗

DOE OSTI2021

Characterizing manufacturing wastewater in the United States for the purpose of analyzing energy requirements for reuse

This paper seeks to inform an improved understanding of the energy tradeoff associated with on-site manufacturing water reuse in the United States from a lifecycle perspective, in part by developing an analytical framework for understanding when this tradeoff for reuse is beneficial. We survey the literature to assess the current state of reuse and its motives and barriers in the United States, before synthesizing information from publicly available EPA data on contaminants in US manufacturing wastewaters and technologies for treating them. Using the available data, we derive a set of “ubiquitous contaminants” among the top ten in terms of mass discharged in more than half of US manufacturing subsectors (NAICS 31–33) according to EPA permit data. We also present information on proven treatment trains and their energy requirements. We then compare water quality requirements for specific contaminants in reclaimed water to those characteristic of wastewater streams currently being discharged from manufacturing plants into surface waters to highlight sectors with reuse opportunities that could require little cost to realize, such as primary metals and, to a lesser extent, petroleum and coal products. We conclude by highlighting data limitations that need to be rectified before applying the framework more broadly and discussing how these data gaps could be filled. Better understanding the relationship between energy and water in the context of on-site manufacturing water reuse would allow manufacturers to improve resiliency by reducing regulatory, physical, and reputational risks while lessening their footprint on local watersheds.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

First Images of the Protoplanetary Disk around PDS 201

Scattered light imaging has revealed nearly a dozen circumstellar disks around young Herbig Ae/Be stars—enabling studies of structures in the upper disk layers as potential signs of ongoing planet formation. We present the first images of the disk around the variable Herbig Ae star PDS 201 (V* V351 Ori) and an analysis of the images and spectral energy distribution through 3D Monte Carlo radiative transfer simulations and forward modeling. The disk is detected in three data sets with the Large Binocular Telescope Interferometer/Large Binocular Telescope mid-infrared camera at the Large Binocular Telescope, including direct observations in the Ks and L′ filters, and an L′ observation with the 360° vector apodizing phase plate coronagraph. The scattered light disk extends to a very large radius of ∼250 au, which places it among the largest of such disks. Exterior to the disk, we establish detection limits on substellar companions down to ∼5 M {sub Jup} at ≳1.″5 (≳500 au), assuming the Baraffe et al. models. The images show a radial gap extending to ∼0.″4 (∼140 au at a distance of 340 pc) that is also evident in the spectral energy distribution. The large gap is a possible signpost of multiple high-mass giant planets at orbital distances (∼60–100 au) that are unusually massive and widely separated compared to those of planet populations previously inferred from protoplanetary disk substructures.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Defect Quantification in Metal Halide Perovskites Anticipates Photoluminescence and Photovoltaic Performance

Semiconductor material optimization requires quantification of performance and stability-dependent near-valence maximum and near-conduction minimum defects with sufficient energy resolution and sensitivity. In this work, we utilize a spectroscopy-electrochemistry approach to resolve the energy-distinct donor and acceptor defect concentrations in wide-gap (Cs .05 FA .79 MA .16 )Pb(I .87 Br .13 ) 3 perovskites, benchmarked against photoluminescence and photovoltaic device performance. Monitoring charge transfer events to electron acceptor and donor molecules within solid electrolyte top contacts enables defect quantification below 10 15 cm –3 at an energy resolution of 10 meV under device-relevant bias, well below levels reported by other methods. Further method sensitivity is demonstrated for defects arising from <2% formamidinium concentration modifications, mimicking compositional imperfections resulting from nonoptimized processing. This method provides the first complete perovskite energetic diagrams with small changes in composition, is nondestructive, compatible with in-line processing characterization, and will enable the semiconductor community to link molecular origins of defects with limitations in device performance across a wide array of optoelectronic platforms.

14 SOLAR ENERGY↗

DOE OSTI2022

Energy-Storing Cryogenic Carbon Capture™ for Utility and Industrial-scale Processes (Final Report)

This project leverages work completed under funding from previous U.S. Department of Energy (DOE) projects and other sources of funding around the Cryogenic Carbon Capture Process™ (CCC). The purpose of this project is to further develop a perturbation of the CCC process that stores energy called the Cryogenic Carbon Capture™ Energy Storing (CCC-ES) process. The successful completion of the tasks in this project has prepared the CCC-ES process for scaling and developed initial plans and a feasibility analysis for an engineering-scale or small-commercial scale system that can store at least 10 MWh of energy. The specific areas of work in this project are: (1) Develop a conceptual, site-specific integrated process flow diagram: Sustainable Energy Solutions (SES) developed a conceptual, site-specific plan including a process flow diagram for integrating CCC-ES at a specific location. The proposed system was based on a typical engineering-scale CCC system designed to capture 30-50 metric tonnes of CO 2 per day (TPD), with modifications and additional changes and equipment put in place to add the energy storage element to the system. The 30-50 TPD scale corresponds to the required 10 MWh of stored energy. This task includes updating simulation software for transient analysis. SES also coordinated with the Jim Bridger Power Plant in Point of Rocks, Wyoming to get site-specific data. Using these data, SES completed site-specific preliminary process flow diagrams, estimated capital and operating costs for the CCC-ES system, and used the upgraded software package to estimate the primary figures of merit. (2) Complete a technoeconomic analysis (TEA): SES completed a full-scale TEA of the CCC-ES system to meet specific success criteria. This TEA used process information from the host site selected above. (3) Technology and data gap assessment for the CCC-ES process: As part of the technology gap assessment, SES performed an assessment of the best alternative energy storage solutions including figures of merit and operational strengths and weaknesses. SES then compared the proposed system with a discussion of how it addresses the weaknesses of alternative systems, showing for example a cost of stored energy at less than $50/MWh and with a roundtrip efficiency of greater than 95%. This assessment includes technical and other risk analyses and technology gaps with research and development needs to commercialize the process by 2030. Finally, work includes a commercialization roadmap/development pathway outlining the major milestones to move to a commercially operating CCC-ES system. (4) Phase II pre-FEED project plan: SES completed a project plan for the Phase II pre-FEED analysis using the same host site as in the Phase I conceptual study.

03 NATURAL GAS↗

DOE OSTI2020

Who Controls Energy in the Smart Home? A Multidisciplinary Taxonomy

Advances in technology have begun to open new opportunities for behavior-based and technical approaches to managing residential energy use and meet sustainability-related objectives. Visions of the future predict homes with smart technologies delivering enhanced comfort and cost savings to residents; utility-partners who can remotely optimize energy resources to meet grid needs; and occupants who play more active roles in the energy system supported by advanced information communication technologies. Each of these scenarios implies augmented control over home energy use, yet uncertainties remain regarding which ones will deliver the greatest grid benefits and services to customers in a given situation. These scenarios also raise broader questions regarding customer agency and the relationship between customers and third parties moving forward. While both the provision of information to spur behavior change and automated technologies theoretically enhance control over energy use in the built environment, these strategies are not often studied from an integrated perspective. Seeking to address this gap and develop a deeper understanding of the evolving paradigm of control over home energy use, this paper presents a taxonomy to evaluate perspectives from public policy (ex. demand-side management), technological innovation (automated controls), and user-agency (ex. the role of behavior change) on approaches to managing home energy use. We draw on theoretical and empirical evidence from across disciplines to detail the dimensions and implications of deploying programs that incorporate various levels of control and anticipate such a taxonomy will help holistically map out and evaluate tradeoffs between different approaches to demand-side management moving forward.

McIlvennie, Claire↗